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Eavesdropping micropredators as dynamic limiters of sexual signal elaboration and intrasexual competition

Citation

Leavell, Brian; Beaty, Lynne; Gordon, McNickle; Ximena, Bernal (2021), Eavesdropping micropredators as dynamic limiters of sexual signal elaboration and intrasexual competition, Dryad, Dataset, https://doi.org/10.5061/dryad.7wm37pvr5

Abstract

To thoroughly understand the drivers of dynamic signal elaboration requires assessing the direct and indirect effects of naturally interacting factors. Here, we use structural equation modeling (SEM) to test multivariate data from in situ observations of sexual signal production against a model of causal processes hypothesized to drive signal elaboration. We assess direct and indirect effects, and relative impacts, of male-male competition and attacks by eavesdropping frog-biting midges (Diptera: Corethrellidae) on call elaboration of male túngara frogs (Engystomops pustulosus). We find that the intensity of attacks by these micropredator flies drives the extent to which frogs elaborate their calls, likely due to a temporal trade-off between signaling and anti-micropredator defense. Micropredator attacks appear to dynamically limit a male’s call rate and complexity and consequently dampen the effects of intrasexual competition. In accounting for naturally interacting drivers of signal elaboration, this study presents a counterpoint to the mechanisms traditionally thought to drive sexual selection in this system. Moreover, the results shed light on the relatively unexamined and potentially influential role of eavesdropping micropredators in the evolution of sexual communication systems.

Methods

In Gamboa, Panamá, during the summers of 2010 and 2012, we observed calling male túngara frogs (Engystomops pustulosusin situ. For each observation, which took place between 1900 and 2300 h, we illuminated a calling male (hereafter, ‘focal frog’) with infrared LED arrays (Sima SL-201R) and recorded audio and video using a Sony DCR-SR220D 120GB Handycam Camcorder. Following an observation, the focal frog was toe-clipped to prevent pseudoreplication and released at point of capture in adherence to protocols established by the American Society of Ichthyologists and Herpetologists (https://asih.org/animal-care-guidelines). We conducted all research in compliance with Panamanian legal and ethical regulations (MiAmbiente collection permits: SE/A-67-10, SC/A-20-12) and following IACUC protocols (Texas Tech University: 11056-08; Smithsonian Tropical Research Institute: 2011-0616-2014-11). See "Methods" in manuscript for more details.

To analyze calling behaviors, we selected a sequence of the first 50 clean, consecutive calls, per focal frog. We used the duration of the sequence, which varied per frog, to derive the call rate—i.e. the total number of calls, minus one, divided by the time from the beginning of the first call to the beginning of the last call. The total number of chucks produced was counted over the same time. To assess the threat of frog-biting midge (Diptera: Corethrellidae) attacks, the total number of instances in which midges landed on the focal frog were counted from video playback during the 50-call sequence. We also counted the total number of times the focal frog swatted during the same sequence. Out of a total of 100 focal frogs that were recorded, we omitted data from fifteen individuals due to high background noise levels or poor video quality that precluded behavioral analysis. The observed dataset thus includes data from a total of 85 males.

Usage Notes

Part of the analysis uses code from:

Zuur AF, Ieno EN, Walker N, et al (2009) Mixed effects models and extensions in ecology with R. Springer New York, New York, NY 

It is available online at: https://highstat.com/Books/BGS/GAMM/RCodeP2/HighstatLibV6.R

Funding

National Science Foundation, Award: IOS#1433990

National Science Foundation, Award: IOS#2054636

National Science Foundation, Award: DGE-1842166